mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-02 20:02:49 +08:00
3c71ab64cc
Summary: The shebang line `#!<path to interpreter>` is only required for Python scripts, so remove it on source files for class or function definitions. Additionally explicitly mark as executable the actual Python scripts in the codebase. Reviewed By: nikhilaravi Differential Revision: D20095778 fbshipit-source-id: d312599fba485e978a243292f88a180d71e1b55a
88 lines
2.4 KiB
Python
88 lines
2.4 KiB
Python
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
|
|
|
|
|
|
from itertools import product
|
|
import torch
|
|
from fvcore.common.benchmark import benchmark
|
|
|
|
from test_rasterize_meshes import TestRasterizeMeshes
|
|
|
|
# ico levels:
|
|
# 0: (12 verts, 20 faces)
|
|
# 1: (42 verts, 80 faces)
|
|
# 3: (642 verts, 1280 faces)
|
|
# 4: (2562 verts, 5120 faces)
|
|
|
|
|
|
def bm_rasterize_meshes() -> None:
|
|
kwargs_list = [
|
|
{
|
|
"num_meshes": 1,
|
|
"ico_level": 0,
|
|
"image_size": 10, # very slow with large image size
|
|
"blur_radius": 0.0,
|
|
}
|
|
]
|
|
benchmark(
|
|
TestRasterizeMeshes.rasterize_meshes_python_with_init,
|
|
"RASTERIZE_MESHES",
|
|
kwargs_list,
|
|
warmup_iters=1,
|
|
)
|
|
|
|
kwargs_list = []
|
|
num_meshes = [1]
|
|
ico_level = [1]
|
|
image_size = [64, 128]
|
|
blur = [0.0, 1e-8, 1e-4]
|
|
test_cases = product(num_meshes, ico_level, image_size, blur)
|
|
for case in test_cases:
|
|
n, ic, im, b = case
|
|
kwargs_list.append(
|
|
{
|
|
"num_meshes": n,
|
|
"ico_level": ic,
|
|
"image_size": im,
|
|
"blur_radius": b,
|
|
}
|
|
)
|
|
benchmark(
|
|
TestRasterizeMeshes.rasterize_meshes_cpu_with_init,
|
|
"RASTERIZE_MESHES",
|
|
kwargs_list,
|
|
warmup_iters=1,
|
|
)
|
|
|
|
if torch.cuda.is_available():
|
|
kwargs_list = []
|
|
num_meshes = [1, 8]
|
|
ico_level = [0, 1, 3, 4]
|
|
image_size = [64, 128, 512]
|
|
blur = [0.0, 1e-8, 1e-4]
|
|
bin_size = [0, 8, 32]
|
|
test_cases = product(num_meshes, ico_level, image_size, blur, bin_size)
|
|
# only keep cases where bin_size == 0 or image_size / bin_size < 16
|
|
test_cases = [
|
|
elem
|
|
for elem in test_cases
|
|
if (elem[-1] == 0 or elem[-3] / elem[-1] < 16)
|
|
]
|
|
for case in test_cases:
|
|
n, ic, im, b, bn = case
|
|
kwargs_list.append(
|
|
{
|
|
"num_meshes": n,
|
|
"ico_level": ic,
|
|
"image_size": im,
|
|
"blur_radius": b,
|
|
"bin_size": bn,
|
|
"max_faces_per_bin": 200,
|
|
}
|
|
)
|
|
benchmark(
|
|
TestRasterizeMeshes.rasterize_meshes_cuda_with_init,
|
|
"RASTERIZE_MESHES_CUDA",
|
|
kwargs_list,
|
|
warmup_iters=1,
|
|
)
|